Abstract
Small proteins characterized by a double-glycine (GG) secretion motif, typical of secreted bacterial antibiotics, are encoded by the genomes of diverse cyanobacteria, but their functions have not been investigated to date. Using a biofilm-forming mutant of Synechococcus elongatus PCC 7942 and a mutational approach, we demonstrate the involvement of four small secreted proteins and their GG-secretion motifs in biofilm development. These proteins are denoted EbfG1-4 (enable biofilm formation with a GG-motif). Furthermore, the conserved cysteine of the peptidase domain of the Synpcc7942-1133 gene product (dubbed PteB for peptidase transporter essential for biofilm) is crucial for biofilm development and is required for efficient secretion of the GG-motif containing proteins. Transcriptional profiling of ebfG1-4 indicated elevated transcript levels in the biofilm-forming mutant compared to wild type (WT). However, these transcripts decreased, acutely but transiently, when the mutant was cultured in extracellular fluids from a WT culture, and biofilm formation was inhibited. We propose that WT cells secrete inhibitor(s) that suppress transcription of ebfG1-4, whereas secretion of the inhibitor(s) is impaired in the biofilm-forming mutant, leading to synthesis and secretion of EbfG1-4 and supporting the formation of biofilms.
Original language | English |
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Article number | 32209 |
Journal | Scientific Reports |
Volume | 6 |
DOIs | |
State | Published - 25 Aug 2016 |
Bibliographical note
Publisher Copyright:© The Author(s) 2016.
Funding
Rakefet Schwarz and Susan Golden are supported by the program of the National Science Foundation and the US-Israel Binational Science Foundation (NSF-BSF 2012823). This study was also supported by a grant from the Israel Science Foundation (ISF 1406/14) to Rakefet Schwarz. We thank Yishai Levin, Meital Kupervaser and Alon Savidor at the de Botton Institute for Protein Profiling, The Nancy and Stephen Grand Israel National Center for Personalised Medicine (Weizmann Institute of Science) for MS analyses. We thank Shlomi Dagan for statistical analysis.
Funders | Funder number |
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NSF-BSF | 2012823 |
National Science Foundation | 1322808 |
Weizmann Institute of Science | |
United States-Israel Binational Science Foundation | |
Israel Science Foundation | ISF 1406/14 |